TY - JOUR
T1 - Fuzzy soft decision CFAR detector for the K distribution data
AU - Xu, Yanwei
AU - Yan, Shefeng
AU - Ma, Xiaochuan
AU - Hou, Chaohuan
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/1
Y1 - 2015/10/1
N2 - A fuzzy statistical normalization fuzzy constant false alarm rate (FSNF-CFAR) detector in a K distribution background based on fuzzy statistical normalization and fuzzy soft decision is proposed. The performance of the proposed fuzzy soft decision detector is studied both for homogeneous backgrounds and for nonhomogeneous environments caused by interfering targets or clutter edges. Performance comparisons with conventional hard decision CFAR detectors such as cell averaging CFAR (CA-CFAR), greater of CFAR (GO-CFAR), and ordered statistics CFAR (OS-CFAR) are carried out. The simulation shows that the proposed FSNF-CFAR detector is simple and efficient, and the comparison results show that it not only can get good detection performance in homogeneous K distribution backgrounds but also can confront interfering targets and clutter edges at the same time in nonhomogeneous environments. Moreover, the fuzzy soft decision detector can provide more valuable information than the hard decision detector for data fusion, target tracking, or object identification.
AB - A fuzzy statistical normalization fuzzy constant false alarm rate (FSNF-CFAR) detector in a K distribution background based on fuzzy statistical normalization and fuzzy soft decision is proposed. The performance of the proposed fuzzy soft decision detector is studied both for homogeneous backgrounds and for nonhomogeneous environments caused by interfering targets or clutter edges. Performance comparisons with conventional hard decision CFAR detectors such as cell averaging CFAR (CA-CFAR), greater of CFAR (GO-CFAR), and ordered statistics CFAR (OS-CFAR) are carried out. The simulation shows that the proposed FSNF-CFAR detector is simple and efficient, and the comparison results show that it not only can get good detection performance in homogeneous K distribution backgrounds but also can confront interfering targets and clutter edges at the same time in nonhomogeneous environments. Moreover, the fuzzy soft decision detector can provide more valuable information than the hard decision detector for data fusion, target tracking, or object identification.
UR - http://www.scopus.com/inward/record.url?scp=84959235870&partnerID=8YFLogxK
U2 - 10.1109/TAES.2015.140817
DO - 10.1109/TAES.2015.140817
M3 - Article
AN - SCOPUS:84959235870
SN - 0018-9251
VL - 51
SP - 3001
EP - 3013
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
IS - 4
M1 - 7376233
ER -
